摘要
针对滤波、相位解缠和多相式拟合法在参数估计中的局限性,提出一种二维多相式相位信号(PPS)参数估计的降维算法。通过固定二维多相式相位信号中的一个参数,将二维PPS转化为一组一维的多相式相位信号,再通过对一维多相式相位信号做滤波和相位解缠等计算处理,最终实现对二维PPS的参数估计;另外,还对该算法的复杂度进行了简单分析。为了验证该算法在高信噪比条件下的有效性,实验采用一个三阶二维PPS的三角式信号模型,仿真结果表明该算法的参数估计均方误差达到Cramér-Rao下界。
In view of the limitations of the methods based on the phase unwrapping,filtering and polynomial fitting,this paper considers the refinement in parameter estimation of 2-D polynomial phase signals（ PPS）. In this method,2-D parameter estimation is reduced to 1-D refinement procedure by fixing a certain parameter of PPS. Then the 1-D PPS are filtered and unwrapped on phase,and ultimately the two-dimensional PPS parameters are estimated. In addition,the complexity of the algorithm is simply evaluated. In order to verify the effectiveness of the algorithm under high signal-to-noise ratio conditions,a third-order two-dimensional PPS is used as a signal model in the experiments.Simulations results show that the mean squared error of the proposed estimator can reach the Cramer-Rio lower bound.
出处
《江南大学学报（自然科学版）》
CAS
2015年第5期580-584,共5页
Joural of Jiangnan University (Natural Science Edition)
基金
福建省自然科学基金项目(2015J01661)
福建省教育厅科技计划A类项目(JA13335)
宁德师范学院服务海西重点项目(2011H102)
宁德师范学院科研创新团队项目(2013T03)
关键词
二维多相式相位信号
相位解缠
参数优化
均方误差
2-D polynomial phase signal
phase unwrapping
parameter refinement
mean squared error
